{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Outlier Filter\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/outlier_filter.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "548dee05a4354189a3a697c88dacae69",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9802467678704a889514fa17ee705bfe",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f155c38d453d417f9c0c2ea9f58c0fb7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/445 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       1958\n",
      "            1,3           3.1          0.920        4.0    4.00       1532\n",
      "          1,3,3           7.1          0.911        7.6    1.90       1264\n",
      "        1,3,3,3          16.5          0.862       10.5    1.38        947\n",
      "      1,3,3,3,3          36.4          0.836       21.6    2.06        639\n",
      "    1,3,3,3,3,3          75.6          0.858       35.5    1.64        348\n",
      "  1,3,3,3,3,3,3         118.5          0.905       38.3    1.08        174\n",
      "              3           1.0          0.977        4.8     inf       4258\n",
      "            3,3           3.3          0.967       11.5    2.40       3851\n",
      "          3,3,3           7.9          0.960       19.6    1.70       3502\n",
      "        3,3,3,3          18.0          0.940       39.9    2.04       2679\n",
      "      3,3,3,3,3          34.3          0.930       47.6    1.19       1669\n",
      "    3,3,3,3,3,3          64.4          0.928       98.5    2.07       1077\n",
      "  3,3,3,3,3,3,3         100.9          0.948      141.7    1.44        526\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.86        131\n",
      "              4           2.0          0.976       10.6     inf       2753\n",
      "            4,3           3.7          0.976       20.0    1.89       2258\n",
      "          4,3,3           8.3          0.967       29.4    1.47       2029\n",
      "        4,3,3,3          19.8          0.957       54.4    1.85       1698\n",
      "      4,3,3,3,3          41.1          0.958       99.5    1.83       1147\n",
      "    4,3,3,3,3,3          68.1          0.956      116.0    1.17        520\n",
      "  4,3,3,3,3,3,3          78.4          0.979      110.6    0.95        247\n",
      "4,3,3,3,3,3,3,3         113.9          0.984      176.6    1.60        165\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    WHERE queue != 0\n",
    "    {\"AND queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_ivl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['create_date'].dt.year < 2006].index, inplace=True)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "\n",
    "def remove_outliers(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    # threshold = np.mean(group['delta_t']) * 1.5\n",
    "    # threshold = group['delta_t'].quantile(0.95)\n",
    "    Q1 = group['delta_t'].quantile(0.25)\n",
    "    Q3 = group['delta_t'].quantile(0.75)\n",
    "    IQR = Q3 - Q1\n",
    "    threshold = Q3 + 1.5 * IQR\n",
    "    group = group[group['delta_t'] < threshold]\n",
    "    return group\n",
    "\n",
    "df[df['i'] == 2] = df[df['i'] == 2].groupby(by=['r_history', 't_history'], as_index=False, group_keys=False).apply(remove_outliers)\n",
    "\n",
    "def remove_non_continuous_rows(group):\n",
    "    discontinuity = group['i'].diff().fillna(1).ne(1)\n",
    "    if not discontinuity.any():\n",
    "        return group\n",
    "    else:\n",
    "        first_non_continuous_index = discontinuity.idxmax()\n",
    "        return group.loc[:first_non_continuous_index-1]\n",
    "\n",
    "df = df.groupby('cid', as_index=False, group_keys=False).progress_apply(remove_non_continuous_rows)\n",
    "\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_ivl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weighted fit parameters: [1.13859448]\n",
      "Number of reviews: 1958\n",
      "RMSE: 0.0218\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weighted fit parameters: [5.45473494]\n",
      "Number of reviews: 4258\n",
      "RMSE: 0.0054\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Weighted fit parameters: [14.90672308]\n",
      "Number of reviews: 2753\n",
      "RMSE: 0.0145\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 1.1385944809379058, 3: 5.454734944907549, 4: 14.90672308187487}\n",
      "Weighted fit parameters: [-1.64529929  1.0769941   0.57210977]\n",
      "Fit stability: [ 1.13859448  5.45473494 14.90672308]\n",
      "RMSE: 0.0000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{1: 1.14, 2: 2.24, 3: 5.45, 4: 14.91}\n"
     ]
    }
   ],
   "source": [
    "from scipy.optimize import curve_fit\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "dataset['y'] = dataset['r'].map({1: 0, 2: 1, 3: 1, 4: 1})\n",
    "S0_dataset = dataset[dataset['i'] == 2]\n",
    "S0_dataset_group = S0_dataset.groupby(by=['r_history', 'delta_t'], group_keys=False).agg({'y': ['mean', 'count']}).reset_index()\n",
    "\n",
    "# we want to find the optimal S\n",
    "def power_curve(delta_t, S):\n",
    "    return (1 + delta_t / (9 * S)) ** -1\n",
    "# def exp_curve(delta_t, S):\n",
    "#     return np.exp(np.log(0.9) * delta_t / S)\n",
    "\n",
    "rating_stability = {}\n",
    "rating_count = {}\n",
    "reviews_in_collection = len(dataset)\n",
    "\n",
    "for first_rating in (\"1\", \"2\", \"3\", \"4\"):\n",
    "    group = S0_dataset_group[S0_dataset_group['r_history'] == first_rating]\n",
    "    if group.empty:\n",
    "        continue\n",
    "    delta_t = group['delta_t']\n",
    "    recall = group['y']['mean']\n",
    "    count = group['y']['count']\n",
    "    if sum(count) < 100:\n",
    "        continue\n",
    "    params, covs = curve_fit(power_curve, delta_t, recall, sigma=1/np.sqrt(count), bounds=((0.1), (3650)))\n",
    "    rating_stability[int(first_rating)] = params[0]\n",
    "    rating_count[int(first_rating)] = sum(count)\n",
    "    print('Weighted fit parameters:', params)\n",
    "    print('Number of reviews:', sum(count))\n",
    "    predict_recall = power_curve(delta_t, *params)\n",
    "    print(f'RMSE: {mean_squared_error(recall, predict_recall, sample_weight=count, squared=False):.4f}')\n",
    "\n",
    "    plt.plot(delta_t, recall, label='Exact')\n",
    "    plt.plot(np.linspace(0, 30), power_curve(np.linspace(0, 30), *params), label='Weighted fit')\n",
    "    count_percent = np.array([x/sum(count) for x in count])\n",
    "    plt.scatter(delta_t, recall, s=count_percent * 1000, alpha=0.5)\n",
    "    plt.legend(loc='upper right', fancybox=True, shadow=False)\n",
    "    plt.grid(True)\n",
    "    plt.ylim(0, 1)\n",
    "    plt.xlim(0, 30)\n",
    "    plt.xlabel('Interval')\n",
    "    plt.ylabel('Recall')\n",
    "    plt.title('Forgetting curve for first rating ' + first_rating)\n",
    "    plt.show()\n",
    "\n",
    "print(rating_stability)\n",
    "\n",
    "def S0_rating_curve(rating, a, b, c):\n",
    "    return np.exp(a + b * rating) + c\n",
    "\n",
    "params, covs = curve_fit(S0_rating_curve, list(rating_stability.keys()), list(rating_stability.values()), sigma=1/np.sqrt(list(rating_count.values())), method='dogbox', bounds=((-15, 0.03, 0), (15, 7, 30)))\n",
    "print('Weighted fit parameters:', params)\n",
    "predict_stability = S0_rating_curve(np.array(list(rating_stability.keys())), *params)\n",
    "print(\"Fit stability:\", predict_stability)\n",
    "print(f'RMSE: {mean_squared_error(list(rating_stability.values()), predict_stability, sample_weight=list(rating_count.values()), squared=False):.4f}')\n",
    "plt.plot(list(rating_stability.keys()), list(rating_stability.values()), label='Exact')\n",
    "plt.plot(list(rating_stability.keys()), predict_stability, label='Weighted fit')\n",
    "plt.legend(loc='upper right', fancybox=True, shadow=False)\n",
    "plt.grid(True)\n",
    "plt.xlabel('First rating')\n",
    "plt.ylabel('Stability')\n",
    "plt.title('Stability for first rating')\n",
    "plt.show()\n",
    "\n",
    "for rating in (1, 2, 3, 4):\n",
    "    again_extrap = max(min(S0_rating_curve(1, *params), 3650), 0.1)\n",
    "    # if there isn't enough data to calculate the value for \"Again\" exactly\n",
    "    if 1 not in rating_stability:\n",
    "        # then check if there exists an exact value for \"Hard\"\n",
    "        if 2 in rating_stability:\n",
    "            # if it exists, then check whether the extrapolation breaks monotonicity\n",
    "            # Again > Hard is possible, but we should allow it only for exact values, otherwise we should assume monotonicity\n",
    "            if again_extrap > rating_stability[2]:\n",
    "                # if it does, then replace the missing \"Again\" value with the exact \"Hard\" value\n",
    "                rating_stability[1] = rating_stability[2]\n",
    "            else:\n",
    "                # if it doesn't break monotonicity, then use the extrapolated value\n",
    "                rating_stability[1] = again_extrap\n",
    "        # if an exact value for \"Hard\" doesn't exist, then just use the extrapolation, there's nothing else we can do\n",
    "        else:\n",
    "            rating_stability[1] = again_extrap\n",
    "    elif rating not in rating_stability:\n",
    "        rating_stability[rating] = max(min(S0_rating_curve(rating, *params), 3650), 0.1)\n",
    "\n",
    "rating_stability = {k: round(v, 2) for k, v in sorted(rating_stability.items(), key=lambda item: item[0])}\n",
    "\n",
    "print(rating_stability)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1, 0.5, 2]\n",
    "\n",
    "def power_forgetting_curve(t, s):\n",
    "    return (1 + t / (9 * s)) ** -1\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "        self.s0 = torch.zeros(4)\n",
    "        for i in range(4):\n",
    "            if i+1 in rating_stability:\n",
    "                self.s0[i] = rating_stability[i+1]\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor, rating: Tensor) -> Tensor:\n",
    "        hard_bonus = torch.where(rating == 2, self.w[13], 1)\n",
    "        easy_bonus = torch.where(rating == 4, self.w[14], 1)\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1) * hard_bonus * easy_bonus)\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * \\\n",
    "                torch.pow(new_d, self.w[10]) * \\\n",
    "                (torch.pow(state[:,0] + 1, self.w[11]) - 1) * \\\n",
    "                torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            keys = torch.tensor([1, 2, 3, 4])\n",
    "            keys = keys.view(1, -1).expand(X[:,1].long().size(0), -1)\n",
    "            index = (X[:,1].long().unsqueeze(1) == keys).nonzero(as_tuple=True)\n",
    "            # first learn, init memory states\n",
    "            new_s = self.s0[index[1]]\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = power_forgetting_curve(X[:,0], state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r, X[:,1]), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.1)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            w[13] = w[13].clamp(0, 1)\n",
    "            w[14] = w[14].clamp(1, 10)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='none')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        best_loss = np.inf\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "                loss = self.loss_fn(retentions, labels).sum()\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels).mean()\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels).mean()\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "92d1590ca20a4fb6b759461e38bd8fcf",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/81504 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 65659 TEST: 15845\n",
      "dataset built\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4e135ec0cb77459c89f890bd384c750c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/283450 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3172\n",
      "Loss in testset: 0.3194\n",
      "iteration: 28160\n",
      "w: [1.0, 1.0, 5.1308, -1.1001, -0.8907, 0.005, 1.4402, -0.1411, 0.8634, 2.2834, -0.0499, 0.3576, 1.1421, 0.0, 2.3793]\n",
      "iteration: 56320\n",
      "w: [1.0, 1.0, 5.3507, -1.5363, -1.0577, 0.0, 1.4802, -0.1459, 0.8953, 2.3389, -0.0409, 0.3163, 0.8509, 0.0, 2.3181]\n",
      "Loss in trainset: 0.2999\n",
      "Loss in testset: 0.3005\n",
      "iteration: 84338\n",
      "w: [1.0, 1.0, 5.3308, -1.5066, -1.0604, 0.0, 1.5701, -0.1, 0.9764, 2.4243, -0.0309, 0.2861, 0.717, 0.0, 2.2202]\n",
      "iteration: 112498\n",
      "w: [1.0, 1.0, 5.3568, -1.3858, -1.1936, 0.0126, 1.5861, -0.1772, 0.9856, 2.5332, -0.01, 0.313, 0.6459, 0.0, 2.267]\n",
      "Loss in trainset: 0.2991\n",
      "Loss in testset: 0.2997\n",
      "iteration: 140516\n",
      "w: [1.0, 1.0, 5.4485, -1.5676, -1.1264, 0.0398, 1.567, -0.1903, 0.9577, 2.5893, -0.0325, 0.3045, 0.554, 0.0, 2.318]\n",
      "iteration: 168676\n",
      "w: [1.0, 1.0, 5.437, -1.4581, -1.261, 0.0074, 1.573, -0.177, 0.9566, 2.6255, -0.0275, 0.3048, 0.4604, 0.0, 2.1894]\n",
      "Loss in trainset: 0.2991\n",
      "Loss in testset: 0.2998\n",
      "iteration: 196694\n",
      "w: [1.0, 1.0, 5.4724, -1.4716, -1.3019, 0.0006, 1.6035, -0.1634, 0.9816, 2.6733, -0.026, 0.3107, 0.4691, 0.0, 2.0411]\n",
      "iteration: 224854\n",
      "w: [1.0, 1.0, 5.4627, -1.4659, -1.2748, 0.007, 1.5987, -0.1698, 0.9734, 2.7105, -0.01, 0.331, 0.4424, 0.0, 2.0445]\n",
      "Loss in trainset: 0.2990\n",
      "Loss in testset: 0.2996\n",
      "iteration: 252872\n",
      "w: [1.0, 1.0, 5.4459, -1.4412, -1.2677, 0.003, 1.5984, -0.1677, 0.9715, 2.707, -0.0178, 0.319, 0.424, 0.0, 2.049]\n",
      "iteration: 281032\n",
      "w: [1.0, 1.0, 5.4482, -1.4475, -1.2671, 0.0048, 1.5998, -0.1646, 0.9726, 2.7071, -0.0176, 0.3184, 0.4206, 0.0, 2.0471]\n",
      "Loss in trainset: 0.2989\n",
      "Loss in testset: 0.2994\n",
      "TRAIN: 64604 TEST: 16900\n",
      "dataset built\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1d5da48affe54ed4be5216dc344fdb3b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/291940 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3202\n",
      "Loss in testset: 0.3078\n",
      "iteration: 29184\n",
      "w: [1.0, 1.0, 5.2668, -1.314, -0.8802, 0.0128, 1.4501, -0.1616, 0.8568, 2.2821, -0.01, 0.3899, 1.1157, 0.0, 2.4886]\n",
      "iteration: 58368\n",
      "w: [1.0, 1.0, 5.4098, -1.3973, -1.1576, 0.0, 1.5137, -0.1264, 0.9254, 2.3316, -0.0178, 0.3174, 0.8763, 0.0, 2.7117]\n",
      "Loss in trainset: 0.3018\n",
      "Loss in testset: 0.2907\n",
      "iteration: 87060\n",
      "w: [1.0, 1.0, 5.3745, -1.5166, -0.9765, 0.0332, 1.4983, -0.1894, 0.9113, 2.4471, -0.0445, 0.319, 0.7748, 0.0, 2.572]\n",
      "iteration: 116244\n",
      "w: [1.0, 1.0, 5.4976, -1.4546, -1.3133, 0.01, 1.6104, -0.1098, 1.0101, 2.5257, -0.0254, 0.3322, 0.7332, 0.0, 2.5359]\n",
      "Loss in trainset: 0.3017\n",
      "Loss in testset: 0.2911\n",
      "iteration: 144936\n",
      "w: [1.0, 1.0, 5.4416, -1.3622, -1.2795, 0.0095, 1.6144, -0.1745, 1.0109, 2.5908, -0.01, 0.3448, 0.6746, 0.0, 2.5258]\n",
      "iteration: 174120\n",
      "w: [1.0, 1.0, 5.5142, -1.5414, -1.2747, 0.0084, 1.6017, -0.1199, 0.993, 2.601, -0.01, 0.3091, 0.5703, 0.0, 2.3591]\n",
      "Loss in trainset: 0.3013\n",
      "Loss in testset: 0.2905\n",
      "iteration: 202812\n",
      "w: [1.0, 1.0, 5.4794, -1.5137, -1.2013, 0.0234, 1.5861, -0.1311, 0.9774, 2.641, -0.0102, 0.3165, 0.5092, 0.0, 2.238]\n",
      "iteration: 231996\n",
      "w: [1.0, 1.0, 5.495, -1.4724, -1.222, 0.0, 1.5666, -0.1734, 0.9578, 2.6625, -0.0165, 0.3194, 0.4941, 0.0, 2.2427]\n",
      "Loss in trainset: 0.3015\n",
      "Loss in testset: 0.2904\n",
      "iteration: 260688\n",
      "w: [1.0, 1.0, 5.4888, -1.4721, -1.2228, 0.0068, 1.5713, -0.1675, 0.9611, 2.665, -0.0127, 0.3138, 0.4709, 0.0, 2.2474]\n",
      "iteration: 289872\n",
      "w: [1.0, 1.0, 5.4901, -1.4726, -1.2255, 0.0058, 1.5732, -0.1654, 0.9627, 2.6685, -0.01, 0.3167, 0.4738, 0.0, 2.2495]\n",
      "Loss in trainset: 0.3012\n",
      "Loss in testset: 0.2904\n",
      "TRAIN: 65379 TEST: 16125\n",
      "dataset built\n"
     ]
    },
    {
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    {
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     "text": [
      "Loss in trainset: 0.3118\n",
      "Loss in testset: 0.3413\n",
      "iteration: 29184\n",
      "w: [1.0, 1.0, 5.2865, -1.3099, -1.1289, 0.0017, 1.438, -0.1312, 0.8635, 2.2854, -0.0126, 0.3717, 1.1863, 0.0, 2.0777]\n",
      "iteration: 58368\n",
      "w: [1.0, 1.0, 5.2888, -1.4047, -1.1258, 0.0489, 1.5732, -0.1373, 0.9879, 2.3317, -0.0164, 0.3027, 0.9444, 0.0, 2.1652]\n",
      "Loss in trainset: 0.2960\n",
      "Loss in testset: 0.3249\n",
      "iteration: 87552\n",
      "w: [1.0, 1.0, 5.3709, -1.543, -1.228, 0.0069, 1.573, -0.1586, 1.0011, 2.4504, -0.0521, 0.3078, 0.8734, 0.0, 2.261]\n",
      "iteration: 116736\n",
      "w: [1.0, 1.0, 5.2842, -1.4108, -1.1409, 0.0369, 1.6081, -0.2139, 1.0308, 2.5115, -0.0305, 0.2915, 0.8008, 0.0, 1.9522]\n",
      "Loss in trainset: 0.2945\n",
      "Loss in testset: 0.3233\n",
      "iteration: 145920\n",
      "w: [1.0, 1.0, 5.3035, -1.5465, -1.1286, 0.0, 1.6119, -0.2078, 1.0331, 2.5824, -0.0499, 0.3043, 0.7252, 0.0, 1.9665]\n",
      "iteration: 175104\n",
      "w: [1.0, 1.0, 5.2921, -1.6155, -0.9854, 0.008, 1.5764, -0.1965, 0.996, 2.6036, -0.0341, 0.2852, 0.6888, 0.0, 1.9478]\n",
      "Loss in trainset: 0.2937\n",
      "Loss in testset: 0.3222\n",
      "iteration: 204288\n",
      "w: [1.0, 1.0, 5.3348, -1.5698, -1.117, 0.0085, 1.5992, -0.1889, 1.0121, 2.6686, -0.0153, 0.3204, 0.6406, 0.0, 1.8565]\n",
      "iteration: 233472\n",
      "w: [1.0, 1.0, 5.3104, -1.5372, -1.093, 0.0, 1.59, -0.1971, 0.9999, 2.6623, -0.0167, 0.2956, 0.6099, 0.0, 1.8872]\n",
      "Loss in trainset: 0.2934\n",
      "Loss in testset: 0.3221\n",
      "iteration: 262656\n",
      "w: [1.0, 1.0, 5.3165, -1.5417, -1.101, 0.0, 1.5911, -0.202, 0.9997, 2.6787, -0.01, 0.3044, 0.6118, 0.0, 1.8708]\n",
      "iteration: 291840\n",
      "w: [1.0, 1.0, 5.3158, -1.5413, -1.0995, 0.0016, 1.592, -0.2013, 1.0003, 2.6818, -0.01, 0.3065, 0.6125, 0.0, 1.8723]\n",
      "Loss in trainset: 0.2933\n",
      "Loss in testset: 0.3221\n",
      "TRAIN: 67289 TEST: 14215\n",
      "dataset built\n"
     ]
    },
    {
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    {
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     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3132\n",
      "Loss in testset: 0.3388\n",
      "iteration: 29184\n",
      "w: [1.0, 1.0, 5.1803, -1.3516, -0.9227, 0.0, 1.4512, -0.1057, 0.8746, 2.2164, -0.0763, 0.3319, 1.0154, 0.0, 2.0994]\n",
      "iteration: 58368\n",
      "w: [1.0, 1.0, 5.3066, -1.4006, -1.0967, 0.0476, 1.4878, -0.1107, 0.9095, 2.4038, -0.01, 0.4102, 0.8578, 0.0, 2.3644]\n",
      "Loss in trainset: 0.2994\n",
      "Loss in testset: 0.3234\n",
      "iteration: 87504\n",
      "w: [1.0, 1.0, 5.3969, -1.421, -1.1724, 0.0359, 1.4713, -0.1185, 0.9002, 2.441, -0.0246, 0.3176, 0.6578, 0.0, 2.72]\n",
      "iteration: 116688\n",
      "w: [1.0, 1.0, 5.4367, -1.5147, -1.1422, 0.0592, 1.4908, -0.1658, 0.911, 2.5266, -0.0286, 0.3431, 0.5654, 0.0059, 2.3073]\n",
      "Loss in trainset: 0.2964\n",
      "Loss in testset: 0.3204\n",
      "iteration: 145824\n",
      "w: [1.0, 1.0, 5.4083, -1.5091, -1.1247, 0.0041, 1.539, -0.1581, 0.9564, 2.5591, -0.0375, 0.3155, 0.5448, 0.0, 2.3361]\n",
      "iteration: 175008\n",
      "w: [1.0, 1.0, 5.3432, -1.5127, -1.0223, 0.0, 1.5683, -0.1108, 0.9813, 2.5987, -0.0294, 0.3078, 0.4583, 0.0, 2.2846]\n",
      "Loss in trainset: 0.2954\n",
      "Loss in testset: 0.3185\n",
      "iteration: 204144\n",
      "w: [1.0, 1.0, 5.464, -1.6491, -1.0949, 0.0253, 1.5381, -0.1325, 0.9528, 2.6514, -0.01, 0.3324, 0.4176, 0.0, 2.2866]\n",
      "iteration: 233328\n",
      "w: [1.0, 1.0, 5.4005, -1.5372, -1.0648, 0.0003, 1.5319, -0.1542, 0.9448, 2.6526, -0.0178, 0.3151, 0.3892, 0.0, 2.2649]\n",
      "Loss in trainset: 0.2949\n",
      "Loss in testset: 0.3187\n",
      "iteration: 262464\n",
      "w: [1.0, 1.0, 5.3916, -1.5242, -1.0667, 0.0, 1.5425, -0.147, 0.9537, 2.665, -0.01, 0.3204, 0.3888, 0.0, 2.2461]\n",
      "iteration: 291648\n",
      "w: [1.0, 1.0, 5.3977, -1.5281, -1.0672, 0.0004, 1.5372, -0.1535, 0.9485, 2.6642, -0.0108, 0.318, 0.3858, 0.0, 2.2424]\n",
      "Loss in trainset: 0.2949\n",
      "Loss in testset: 0.3185\n",
      "TRAIN: 63085 TEST: 18419\n",
      "dataset built\n"
     ]
    },
    {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3263\n",
      "Loss in testset: 0.2882\n",
      "iteration: 29184\n",
      "w: [1.0, 1.0, 5.3857, -1.3353, -0.9785, 0.0182, 1.4276, -0.1654, 0.829, 2.2886, -0.0286, 0.3588, 1.0144, 0.0, 2.1322]\n",
      "iteration: 58368\n",
      "w: [1.0, 1.0, 5.2625, -1.2036, -0.9239, 0.0, 1.4882, -0.1977, 0.9359, 2.3749, -0.0283, 0.3138, 0.9501, 0.0, 2.135]\n",
      "Loss in trainset: 0.3074\n",
      "Loss in testset: 0.2722\n",
      "iteration: 87046\n",
      "w: [1.0, 1.0, 5.2375, -1.4129, -0.8552, 0.0, 1.5266, -0.1647, 0.9785, 2.5034, -0.01, 0.3461, 0.7908, 0.0, 2.1428]\n",
      "iteration: 116230\n",
      "w: [1.0, 1.0, 5.3825, -1.4027, -1.1269, 0.0121, 1.522, -0.1832, 0.9668, 2.5492, -0.0282, 0.284, 0.7448, 0.0, 2.2232]\n",
      "Loss in trainset: 0.3085\n",
      "Loss in testset: 0.2732\n",
      "iteration: 144908\n",
      "w: [1.0, 1.0, 5.4147, -1.269, -1.2496, 0.0064, 1.5545, -0.162, 0.9908, 2.6753, -0.01, 0.3564, 0.7255, 0.0, 2.1396]\n",
      "iteration: 174092\n",
      "w: [1.0, 1.0, 5.5161, -1.53, -1.2249, 0.0126, 1.5263, -0.1686, 0.9624, 2.6753, -0.0321, 0.3189, 0.6421, 0.0, 2.0519]\n",
      "Loss in trainset: 0.3072\n",
      "Loss in testset: 0.2718\n",
      "iteration: 202770\n",
      "w: [1.0, 1.0, 5.4694, -1.5073, -1.1987, 0.0197, 1.5709, -0.1419, 1.0035, 2.6951, -0.01, 0.297, 0.5859, 0.0, 2.0806]\n",
      "iteration: 231954\n",
      "w: [1.0, 1.0, 5.4789, -1.5081, -1.1926, 0.0, 1.5546, -0.1654, 0.9858, 2.7363, -0.0124, 0.3215, 0.5908, 0.0, 1.9826]\n",
      "Loss in trainset: 0.3070\n",
      "Loss in testset: 0.2717\n",
      "iteration: 260632\n",
      "w: [1.0, 1.0, 5.4794, -1.5154, -1.1859, 0.0083, 1.5523, -0.1681, 0.9824, 2.7209, -0.0287, 0.2962, 0.5522, 0.0, 1.9827]\n",
      "iteration: 289816\n",
      "w: [1.0, 1.0, 5.4757, -1.5123, -1.1844, 0.0076, 1.5559, -0.1659, 0.9856, 2.728, -0.0207, 0.3027, 0.5568, 0.0, 1.979]\n",
      "Loss in trainset: 0.3070\n",
      "Loss in testset: 0.2717\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 5\n",
    "n_splits: int = 5\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.0, 1.0, 5.4255, -1.5004, -1.1687, 0.004, 1.5716, -0.1701, 0.9739, 2.6899, -0.0138, 0.3125, 0.4899, 0.0, 2.0781]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,1d,2d,5d,10d,18d,1.1m,1.9m,3.1m,5.0m,7.8m\n",
      "difficulty history: 0,8.4,8.4,8.4,8.4,8.4,8.4,8.4,8.3,8.3,8.3\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,2d,6d,15d,1.1m,2.4m,4.7m,8.9m,1.3y,2.2y,3.7y\n",
      "difficulty history: 0,6.9,6.9,6.9,6.9,6.9,6.9,6.9,6.9,6.9,6.9\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,5d,16d,1.4m,3.5m,7.9m,1.3y,2.6y,4.9y,8.6y,14.7y\n",
      "difficulty history: 0,5.4,5.4,5.4,5.4,5.4,5.4,5.4,5.4,5.4,5.4\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,15d,1.6m,4.5m,11.2m,2.1y,4.5y,8.9y,16.7y,29.8y,51.0y\n",
      "difficulty history: 0,3.9,3.9,3.9,3.9,3.9,4.0,4.0,4.0,4.0,4.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.4500, 5.4255])\n",
      "tensor([15.7842,  5.4255])\n",
      "tensor([43.2347,  5.4255])\n",
      "tensor([105.4535,   5.4255])\n",
      "tensor([235.9946,   5.4255])\n",
      "tensor([12.4188,  7.7536])\n",
      "tensor([ 3.4189, 10.0000])\n",
      "tensor([4.6478, 9.9817])\n",
      "tensor([6.6048, 9.9635])\n",
      "tensor([9.2332, 9.9453])\n",
      "tensor([12.4954,  9.9272])\n",
      "tensor([16.6996,  9.9092])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,5,16,43,105,236,12,3,5,7,9,12,17\n",
      "difficulty history: 0,5.4,5.4,5.4,5.4,5.4,7.8,10.0,10.0,10.0,9.9,9.9,9.9\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3176, loss after: 0.2990, improvement: 0.0187\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9607\n",
      "RMSE: 0.0152\n",
      "[0.03692685 0.96045056]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.4518\n",
      "RMSE: 0.0412\n",
      "[0.29491295 0.65847309]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: 0.5793\n",
      "RMSE: 0.0547\n",
      "[0.03217689 0.91359513]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9552\n",
      "RMSE: 0.0168\n",
      "[0.0096805  0.99827366]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: 0.6987\n",
      "RMSE: 0.0165\n",
      "[0.15394988 0.83751261]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_3d59e_row0_col0, #T_3d59e_row0_col1, #T_3d59e_row0_col2, #T_3d59e_row0_col3, #T_3d59e_row0_col4, #T_3d59e_row0_col5, #T_3d59e_row0_col6, #T_3d59e_row1_col0, #T_3d59e_row1_col1, #T_3d59e_row1_col2, #T_3d59e_row1_col3, #T_3d59e_row1_col4, #T_3d59e_row1_col6, #T_3d59e_row2_col0, #T_3d59e_row2_col1, #T_3d59e_row2_col2, #T_3d59e_row2_col3, #T_3d59e_row2_col4, #T_3d59e_row2_col5, #T_3d59e_row2_col6, #T_3d59e_row3_col0, #T_3d59e_row3_col1, #T_3d59e_row3_col2, #T_3d59e_row3_col3, #T_3d59e_row3_col4, #T_3d59e_row3_col6, #T_3d59e_row4_col0, #T_3d59e_row4_col1, #T_3d59e_row4_col2, #T_3d59e_row4_col3, #T_3d59e_row4_col4, #T_3d59e_row4_col6, #T_3d59e_row5_col0, #T_3d59e_row5_col1, #T_3d59e_row5_col2, #T_3d59e_row5_col3, #T_3d59e_row5_col4, #T_3d59e_row6_col0, #T_3d59e_row6_col1, #T_3d59e_row7_col0, #T_3d59e_row7_col1, #T_3d59e_row8_col0, #T_3d59e_row8_col1, #T_3d59e_row9_col0, #T_3d59e_row9_col3, #T_3d59e_row10_col0, #T_3d59e_row11_col3, #T_3d59e_row12_col3, #T_3d59e_row13_col0, #T_3d59e_row13_col3, #T_3d59e_row13_col6, #T_3d59e_row14_col0, #T_3d59e_row14_col3, #T_3d59e_row14_col6, #T_3d59e_row14_col7, #T_3d59e_row15_col0, #T_3d59e_row15_col3, #T_3d59e_row15_col5, #T_3d59e_row15_col6, #T_3d59e_row15_col7, #T_3d59e_row16_col0, #T_3d59e_row16_col3, #T_3d59e_row16_col4, #T_3d59e_row16_col5, #T_3d59e_row16_col6, #T_3d59e_row16_col7, #T_3d59e_row17_col0, #T_3d59e_row17_col2, #T_3d59e_row17_col3, #T_3d59e_row17_col4, #T_3d59e_row17_col5, #T_3d59e_row17_col6, #T_3d59e_row17_col7 {\n",
       "  background-color: #000000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row0_col7, #T_3d59e_row16_col2 {\n",
       "  background-color: #9191ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row1_col5, #T_3d59e_row12_col5 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row1_col7 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row2_col7 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row3_col5 {\n",
       "  background-color: #a5a5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row3_col7, #T_3d59e_row14_col2 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row4_col5, #T_3d59e_row6_col7, #T_3d59e_row9_col4, #T_3d59e_row9_col7, #T_3d59e_row10_col1 {\n",
       "  background-color: #f9f9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row4_col7, #T_3d59e_row6_col3, #T_3d59e_row8_col4, #T_3d59e_row11_col0, #T_3d59e_row15_col1 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row5_col5, #T_3d59e_row8_col3, #T_3d59e_row9_col6, #T_3d59e_row10_col3 {\n",
       "  background-color: #fdfdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row5_col6 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row5_col7, #T_3d59e_row9_col1, #T_3d59e_row11_col2 {\n",
       "  background-color: #fff5f5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row6_col2 {\n",
       "  background-color: #fffdfd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row6_col4 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row6_col5 {\n",
       "  background-color: #d5d5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row6_col6 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col2, #T_3d59e_row8_col2 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col3, #T_3d59e_row11_col6 {\n",
       "  background-color: #ffe5e5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col4, #T_3d59e_row11_col7 {\n",
       "  background-color: #ffd5d5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col5, #T_3d59e_row14_col4 {\n",
       "  background-color: #ffbdbd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col6 {\n",
       "  background-color: #ffc1c1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row7_col7, #T_3d59e_row14_col1 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row8_col5, #T_3d59e_row8_col6, #T_3d59e_row10_col7 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row8_col7, #T_3d59e_row13_col5 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row9_col2 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row9_col5 {\n",
       "  background-color: #ffb1b1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row10_col2 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row10_col4, #T_3d59e_row12_col4 {\n",
       "  background-color: #ffc5c5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row10_col5 {\n",
       "  background-color: #ff8181;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row10_col6 {\n",
       "  background-color: #ff8585;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row11_col1, #T_3d59e_row12_col7, #T_3d59e_row13_col1 {\n",
       "  background-color: #ededff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row11_col4 {\n",
       "  background-color: #ff9d9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row11_col5 {\n",
       "  background-color: #ffb9b9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row12_col0, #T_3d59e_row15_col2 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row12_col1, #T_3d59e_row17_col1 {\n",
       "  background-color: #e1e1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row12_col2 {\n",
       "  background-color: #ffd1d1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row12_col6 {\n",
       "  background-color: #ffb5b5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row13_col2 {\n",
       "  background-color: #ffe1e1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row13_col4 {\n",
       "  background-color: #ff9595;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3d59e_row13_col7 {\n",
       "  background-color: #0909ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row14_col5 {\n",
       "  background-color: #9999ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row15_col4 {\n",
       "  background-color: #9d9dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3d59e_row16_col1 {\n",
       "  background-color: #a1a1ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_3d59e\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_3d59e_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
       "      <th id=\"T_3d59e_level0_col1\" class=\"col_heading level0 col1\" >4</th>\n",
       "      <th id=\"T_3d59e_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
       "      <th id=\"T_3d59e_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
       "      <th id=\"T_3d59e_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
       "      <th id=\"T_3d59e_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
       "      <th id=\"T_3d59e_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
       "      <th id=\"T_3d59e_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "      <th class=\"blank col7\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row0\" class=\"row_heading level0 row0\" >0.710000</th>\n",
       "      <td id=\"T_3d59e_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col6\" class=\"data row0 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row0_col7\" class=\"data row0 col7\" >-4.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row1\" class=\"row_heading level0 row1\" >1.000000</th>\n",
       "      <td id=\"T_3d59e_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col5\" class=\"data row1 col5\" >0.57%</td>\n",
       "      <td id=\"T_3d59e_row1_col6\" class=\"data row1 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row1_col7\" class=\"data row1 col7\" >-2.83%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row2\" class=\"row_heading level0 row2\" >1.400000</th>\n",
       "      <td id=\"T_3d59e_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col4\" class=\"data row2 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col5\" class=\"data row2 col5\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col6\" class=\"data row2 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row2_col7\" class=\"data row2 col7\" >-3.21%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row3\" class=\"row_heading level0 row3\" >1.960000</th>\n",
       "      <td id=\"T_3d59e_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col3\" class=\"data row3 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col4\" class=\"data row3 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col5\" class=\"data row3 col5\" >-3.59%</td>\n",
       "      <td id=\"T_3d59e_row3_col6\" class=\"data row3 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row3_col7\" class=\"data row3 col7\" >-1.47%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row4\" class=\"row_heading level0 row4\" >2.740000</th>\n",
       "      <td id=\"T_3d59e_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col3\" class=\"data row4 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col4\" class=\"data row4 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col5\" class=\"data row4 col5\" >-0.22%</td>\n",
       "      <td id=\"T_3d59e_row4_col6\" class=\"data row4 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row4_col7\" class=\"data row4 col7\" >-0.85%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row5\" class=\"row_heading level0 row5\" >3.840000</th>\n",
       "      <td id=\"T_3d59e_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row5_col1\" class=\"data row5 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row5_col2\" class=\"data row5 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row5_col3\" class=\"data row5 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row5_col4\" class=\"data row5 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row5_col5\" class=\"data row5 col5\" >-0.08%</td>\n",
       "      <td id=\"T_3d59e_row5_col6\" class=\"data row5 col6\" >2.03%</td>\n",
       "      <td id=\"T_3d59e_row5_col7\" class=\"data row5 col7\" >0.42%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row6\" class=\"row_heading level0 row6\" >5.380000</th>\n",
       "      <td id=\"T_3d59e_row6_col0\" class=\"data row6 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row6_col1\" class=\"data row6 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row6_col2\" class=\"data row6 col2\" >0.14%</td>\n",
       "      <td id=\"T_3d59e_row6_col3\" class=\"data row6 col3\" >-0.91%</td>\n",
       "      <td id=\"T_3d59e_row6_col4\" class=\"data row6 col4\" >-0.51%</td>\n",
       "      <td id=\"T_3d59e_row6_col5\" class=\"data row6 col5\" >-1.63%</td>\n",
       "      <td id=\"T_3d59e_row6_col6\" class=\"data row6 col6\" >-1.25%</td>\n",
       "      <td id=\"T_3d59e_row6_col7\" class=\"data row6 col7\" >-0.20%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row7\" class=\"row_heading level0 row7\" >7.530000</th>\n",
       "      <td id=\"T_3d59e_row7_col0\" class=\"data row7 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row7_col1\" class=\"data row7 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row7_col2\" class=\"data row7 col2\" >-2.03%</td>\n",
       "      <td id=\"T_3d59e_row7_col3\" class=\"data row7 col3\" >0.95%</td>\n",
       "      <td id=\"T_3d59e_row7_col4\" class=\"data row7 col4\" >1.67%</td>\n",
       "      <td id=\"T_3d59e_row7_col5\" class=\"data row7 col5\" >2.51%</td>\n",
       "      <td id=\"T_3d59e_row7_col6\" class=\"data row7 col6\" >2.46%</td>\n",
       "      <td id=\"T_3d59e_row7_col7\" class=\"data row7 col7\" >0.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row8\" class=\"row_heading level0 row8\" >10.540000</th>\n",
       "      <td id=\"T_3d59e_row8_col0\" class=\"data row8 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row8_col1\" class=\"data row8 col1\" ></td>\n",
       "      <td id=\"T_3d59e_row8_col2\" class=\"data row8 col2\" >-1.95%</td>\n",
       "      <td id=\"T_3d59e_row8_col3\" class=\"data row8 col3\" >-0.13%</td>\n",
       "      <td id=\"T_3d59e_row8_col4\" class=\"data row8 col4\" >-0.84%</td>\n",
       "      <td id=\"T_3d59e_row8_col5\" class=\"data row8 col5\" >1.50%</td>\n",
       "      <td id=\"T_3d59e_row8_col6\" class=\"data row8 col6\" >1.48%</td>\n",
       "      <td id=\"T_3d59e_row8_col7\" class=\"data row8 col7\" >2.02%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row9\" class=\"row_heading level0 row9\" >14.760000</th>\n",
       "      <td id=\"T_3d59e_row9_col0\" class=\"data row9 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row9_col1\" class=\"data row9 col1\" >0.36%</td>\n",
       "      <td id=\"T_3d59e_row9_col2\" class=\"data row9 col2\" >0.70%</td>\n",
       "      <td id=\"T_3d59e_row9_col3\" class=\"data row9 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row9_col4\" class=\"data row9 col4\" >-0.16%</td>\n",
       "      <td id=\"T_3d59e_row9_col5\" class=\"data row9 col5\" >3.10%</td>\n",
       "      <td id=\"T_3d59e_row9_col6\" class=\"data row9 col6\" >-0.14%</td>\n",
       "      <td id=\"T_3d59e_row9_col7\" class=\"data row9 col7\" >-0.26%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row10\" class=\"row_heading level0 row10\" >20.660000</th>\n",
       "      <td id=\"T_3d59e_row10_col0\" class=\"data row10 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row10_col1\" class=\"data row10 col1\" >-0.28%</td>\n",
       "      <td id=\"T_3d59e_row10_col2\" class=\"data row10 col2\" >-0.35%</td>\n",
       "      <td id=\"T_3d59e_row10_col3\" class=\"data row10 col3\" >-0.08%</td>\n",
       "      <td id=\"T_3d59e_row10_col4\" class=\"data row10 col4\" >2.31%</td>\n",
       "      <td id=\"T_3d59e_row10_col5\" class=\"data row10 col5\" >4.90%</td>\n",
       "      <td id=\"T_3d59e_row10_col6\" class=\"data row10 col6\" >4.73%</td>\n",
       "      <td id=\"T_3d59e_row10_col7\" class=\"data row10 col7\" >1.45%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row11\" class=\"row_heading level0 row11\" >28.930000</th>\n",
       "      <td id=\"T_3d59e_row11_col0\" class=\"data row11 col0\" >-0.82%</td>\n",
       "      <td id=\"T_3d59e_row11_col1\" class=\"data row11 col1\" >-0.75%</td>\n",
       "      <td id=\"T_3d59e_row11_col2\" class=\"data row11 col2\" >0.38%</td>\n",
       "      <td id=\"T_3d59e_row11_col3\" class=\"data row11 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row11_col4\" class=\"data row11 col4\" >3.78%</td>\n",
       "      <td id=\"T_3d59e_row11_col5\" class=\"data row11 col5\" >2.68%</td>\n",
       "      <td id=\"T_3d59e_row11_col6\" class=\"data row11 col6\" >1.08%</td>\n",
       "      <td id=\"T_3d59e_row11_col7\" class=\"data row11 col7\" >1.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row12\" class=\"row_heading level0 row12\" >40.500000</th>\n",
       "      <td id=\"T_3d59e_row12_col0\" class=\"data row12 col0\" >-2.05%</td>\n",
       "      <td id=\"T_3d59e_row12_col1\" class=\"data row12 col1\" >-1.16%</td>\n",
       "      <td id=\"T_3d59e_row12_col2\" class=\"data row12 col2\" >1.86%</td>\n",
       "      <td id=\"T_3d59e_row12_col3\" class=\"data row12 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row12_col4\" class=\"data row12 col4\" >2.29%</td>\n",
       "      <td id=\"T_3d59e_row12_col5\" class=\"data row12 col5\" >0.62%</td>\n",
       "      <td id=\"T_3d59e_row12_col6\" class=\"data row12 col6\" >2.83%</td>\n",
       "      <td id=\"T_3d59e_row12_col7\" class=\"data row12 col7\" >-0.68%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row13\" class=\"row_heading level0 row13\" >56.690000</th>\n",
       "      <td id=\"T_3d59e_row13_col0\" class=\"data row13 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row13_col1\" class=\"data row13 col1\" >-0.69%</td>\n",
       "      <td id=\"T_3d59e_row13_col2\" class=\"data row13 col2\" >1.25%</td>\n",
       "      <td id=\"T_3d59e_row13_col3\" class=\"data row13 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row13_col4\" class=\"data row13 col4\" >4.06%</td>\n",
       "      <td id=\"T_3d59e_row13_col5\" class=\"data row13 col5\" >1.89%</td>\n",
       "      <td id=\"T_3d59e_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row13_col7\" class=\"data row13 col7\" >-9.62%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row14\" class=\"row_heading level0 row14\" >79.370000</th>\n",
       "      <td id=\"T_3d59e_row14_col0\" class=\"data row14 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row14_col1\" class=\"data row14 col1\" >0.19%</td>\n",
       "      <td id=\"T_3d59e_row14_col2\" class=\"data row14 col2\" >-1.52%</td>\n",
       "      <td id=\"T_3d59e_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row14_col4\" class=\"data row14 col4\" >2.56%</td>\n",
       "      <td id=\"T_3d59e_row14_col5\" class=\"data row14 col5\" >-3.97%</td>\n",
       "      <td id=\"T_3d59e_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row14_col7\" class=\"data row14 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row15\" class=\"row_heading level0 row15\" >111.120000</th>\n",
       "      <td id=\"T_3d59e_row15_col0\" class=\"data row15 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row15_col1\" class=\"data row15 col1\" >-0.83%</td>\n",
       "      <td id=\"T_3d59e_row15_col2\" class=\"data row15 col2\" >-2.12%</td>\n",
       "      <td id=\"T_3d59e_row15_col3\" class=\"data row15 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row15_col4\" class=\"data row15 col4\" >-3.88%</td>\n",
       "      <td id=\"T_3d59e_row15_col5\" class=\"data row15 col5\" ></td>\n",
       "      <td id=\"T_3d59e_row15_col6\" class=\"data row15 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row15_col7\" class=\"data row15 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row16\" class=\"row_heading level0 row16\" >155.570000</th>\n",
       "      <td id=\"T_3d59e_row16_col0\" class=\"data row16 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row16_col1\" class=\"data row16 col1\" >-3.72%</td>\n",
       "      <td id=\"T_3d59e_row16_col2\" class=\"data row16 col2\" >-4.24%</td>\n",
       "      <td id=\"T_3d59e_row16_col3\" class=\"data row16 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row16_col4\" class=\"data row16 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row16_col5\" class=\"data row16 col5\" ></td>\n",
       "      <td id=\"T_3d59e_row16_col6\" class=\"data row16 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row16_col7\" class=\"data row16 col7\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3d59e_level0_row17\" class=\"row_heading level0 row17\" >217.800000</th>\n",
       "      <td id=\"T_3d59e_row17_col0\" class=\"data row17 col0\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col1\" class=\"data row17 col1\" >-1.14%</td>\n",
       "      <td id=\"T_3d59e_row17_col2\" class=\"data row17 col2\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col3\" class=\"data row17 col3\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col4\" class=\"data row17 col4\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col5\" class=\"data row17 col5\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col6\" class=\"data row17 col6\" ></td>\n",
       "      <td id=\"T_3d59e_row17_col7\" class=\"data row17 col7\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2d0cea580>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.03806557480188666\n",
      "R-squared: -5.7995\n",
      "RMSE: 0.1447\n",
      "[0.67776429 0.26547246]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0079\n",
      "Universal Metric of SM2: 0.0693\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
